Palabras clave
aprendizaje automático
aprendizaje profundo
matrículas
detección automática
Cómo citar
Resumen
La visión artificial es uno de los campos de la Inteligencia Artificial que está en auge debido a que se centra en el desarrollo y mejoramiento de técnicas que permiten a las computadoras identificar, procesar y clasificar las imágenes de una manera similar a lo que hace la visión humana. Esta característica los vuelve una excelente herramienta para los sistemas de control vehicular. Por ello, nosotros desarrollamos un sistema para el reconocimiento de matrículas de la Ciudad de México mediante técnicas de visión artificial, procesamiento de imágenes y aprendizaje automático, con la finalidad de monitorear y agilizar los tiempos de respuesta en caso de encontrar un vehículo robado.
Citas
Ahmed, S., Tan, T. M., Mondol, A. M., Alam, Z., Nawal, N., & Uddin, J. (2019). Automated toll collection system based on rfid sensor. In 2019 International Carnahan Conference on Security Technology (ICCST) (pp. 1-3). IEEE.
Asif, M. R., Chun, Q., Hussain, S., Fareed, M. S., & Khan, S. (2017). Multinational vehicle license plate detection in complex backgrounds. Journal of Visual Communication and Image Representation, 46, 176-186.
Benitez-Garcia, G., Prudente-Tixteco, L., Castro-Madrid, L. C., Toscano-Medina, R., Olivares-Mercado, J., Sanchez-Perez, G., & Villalba, L. J. G. (2021). Improving real-time hand gesture recognition with semantic segmentation. Sensors, 21(2), 356.
Blythe, P. T. (2004). Improving public transport ticketing through smart cards. In Proceedings of the Institution of Civil Engineers-Municipal Engineer (Vol. 157, No. 1, pp. 47-54). Thomas Telford Ltd.
Calero, M. J. F., Sanchez, M. A., Vargas, J., & Ayala, M. J. (2021). Ecuadorian regulatory traffic sign detection by using HOG features and ELM classifier. IEEE Latin America Transactions, 19(4), 634-642.
Dang, T., Gupta, V., Wadia, D. S., Kohli, P., & Chahal, R. K. (2021, March). FaceIgnition: An automatic anti-theft and keyless solution for vehicles. In 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE) (pp. 248-253). IEEE.
Darapaneni, N., Mogeraya, K., Mandal, S., Narayanan, A., Siva, P., Paduri, A. R., & Agadi, P. M. (2020). Computer vision based license plate detection for automated vehicle parking management system. In 2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) (pp. 0800-0805). IEEE.
Díaz-Parra, O., Ruiz-Vanoye, J. A., Fuentes-Penna, A., Zezzatti, A. O., Cruz-Hernández, E., Estrada-García, S., & Alvarado-Pérez, A. (2020). Editorial for Volume 11 Number 2: Electric School Bus Routing Problem for Smart Cities. International Journal of Combinatorial Optimization Problems and Informatics, 11(2), 1.
Diaz-Ramirez, V. H., & Juarez-Salazar, R. (2021, August). Multiple object tracking in color scenes using composite-matched filtering with complex constrains. In Optics and Photonics for Information Processing XV (Vol. 11841, p. 118410J). International Society for Optics and Photonics
Farag, M. S., El Din, M. M., & El Shenbary, H. A. (2019). Parking entrance control using license plate detection and recognition. Indonesian Journal of Electrical Engineering and Computer Science, 15(1), 476-483.
Gupta, A., Gandhi, C., Katara, V., & Brar, S. (2020). Real-time video monitoring of vehicular traffic and adaptive signal change using Raspberry Pi. In 2020 IEEE Students Conference on Engineering & Systems (SCES) (pp. 1-5). IEEE.
Janai, J., Güney, F., Behl, A., & Geiger, A. (2020). Computer vision for autonomous vehicles: Problems, datasets and state of the art. Foundations and Trends in Computer Graphics and Vision, 12(1–3), 1-308.
Karande, J., & Joshi, S. (2020, July). Real-Time Detection of Cyber Attacks on the IoT Devices. In 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE.
Le, H., Liu, F., Zhang, S., & Agarwala, A. (2020). Deep homography estimation for dynamic scenes. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 7652-7661).
Liu, W., Wei, J., & Meng, Q. (2020). Comparisions on KNN, SVM, BP and the CNN for Handwritten Digit Recognition. In 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA) (pp. 587-590). IEEE.
López-Monroy, A. P., Elias-Miranda, A. A., Vallejo-Aldana, D., García-Carmona, J. M., & Pérez-Espinosa, H. (2021). Deep Learning for Language and Vision Tasks in Surveillance Applications. Computación y Sistemas, 25(2), 317-328.
Makkar, T., Kumar, Y., Dubey, A. K., Rocha, Á., & Goyal, A. (2017). Analogizing time complexity of KNN and CNN in recognizing handwritten digits. In 2017 Fourth International Conference on Image Information Processing (ICIIP) (pp. 1-6). IEEE.
Martínez-Cruz, A., Ramírez-Gutiérrez, K. A., Feregrino-Uribe, C., & Morales-Reyes, A. (2021). Security on in-vehicle communication protocols: Issues, challenges, and future research directions. Computer Communications.
Mattoo, A., Saxena, K., Kumar, S., & Bagwari, N. (2021). Design of IoT-Based Smart Illumination System in Smart Cities. In Proceedings of 3rd International Conference on Computing Informatics and Networks (pp. 517-528). Springer, Singapore.
Mirmozaffari, M. (2020). Filtering in image processing. ENG transactions, vol 1. Mo, S., Gan, H., Zhang, R., Yan, Y., & Liu, X. (2020, June). Edge Detection Method Based on Hysteresis Connection and Prediction. In 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) (Vol. 1, pp. 1794-1798). IEEE.
Prasad, S. K., Rachna, J., Khalaf, O. I., & Le, D. N. (2020). Map matching algorithm: Real time location tracking for smart security application. Telecommunications and Radio Engineering, 79(13).
Prongnuch, S., & Sitjongsataporn, S. (2020). Thai voice-controlled analysis for car parking assistance in system-on-chip architecture. Advances in Technology Innovation, 5(4), 203.
Receveur, J. B., Victor, S., & Melchior, P. (2020). Autonomous car decision making and trajectory tracking based on genetic algorithms and fractional potential fields. Intelligent Service Robotics, 13(2), 315-330.
Rodríguez, R. C., Carlos, C. M., Vergara-Villegas, O. O., & Sánchez, V. G. C. (2020). Detección y clasificación de señales de tráfico mexicanas mediante aprendizaje profundo. Res. Comput. Sci., 149(8), 435-449.
San Hlaing, N. N., Naing, M., & San Naing, S. (2019). GPS and GSM based vehicle tracking system. International Journal of Trend in Scientific Research and Development (IJTSRD).
Sathiskumar, S., Navean, G. V., Hari Prakash, R., & Vishnu Praveen, S. (2020). Automatic Vehicle Speed Control System In A Restricted Zone. International Journal Of Scientific & Technology Research, 9(02).
Selmi, Z., Halima, M. B., Pal, U., & Alimi, M. A. (2020). DELP-DAR system for license plate detection and recognition. Pattern Recognition Letters, 129, 213-223.
Shashirangana, J., Padmasiri, H., Meedeniya, D., & Perera, C. (2020). Automated license plate recognition: a survey on methods and techniques. IEEE Access, 9, 11203-11225.
Shukla, A., & Jain, A. (2018). GPS-Based Tracking System for Vehicles Using Google Maps. IUP Journal of Electrical and Electronics Engineering, 11(4), 57-64.
Valencia, J., Ramirez-Guerrero, T., Castañeda, L., & Toro, M. (2020). Detección de infracciones y matrículas en motocicletas, mediante visión artificial, aplicado a Sistemas Inteligentes de Transporte. Revista Ibérica de Sistemas e Tecnologias de Informação, (37), 1-15.
Vazquez-Nicolas, J. M., Zamora, E., González-Hernández, I., Lozano, R., & Sossa, H. (2020). PD+ SMC quadrotor control for altitude and crack recognition using deep learning. International Journal of Control, Automation and Systems, 18(4), 834-844.
Vijayalakshmi, N., Shrinithi, R., Sanjana, V., & Sowmiya, T. (2021, March). Vehicle Tracking and Locking System Based on GSM and GPS. In 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS) (Vol. 1, pp. 758-761). IEEE.
Virgilio G, V. R., Sossa, H., & Zamora, E. (2020). Vision-based blind spot warning system by deep neural networks. In Mexican Conference on Pattern Recognition (pp. 185-194). Springer, Cham.
Weihong, W., & Jiaoyang, T. (2020). Research on license plate recognition algorithms based on deep learning in complex environment. IEEE Access, 8, 91661-91675.
Wijaya, K. T., Bharoto, L. Y., Purwanto, A., & Syamsuddin, E. Y. (2020). Vision-based parking assist system with bird-eye surround vision for reverse bay parking maneuver recommendation. In 2020 International Electronics Symposium (IES) (pp. 102-107). IEEE.
Wijnhoven, R. G., & de With, P. H. (2011). Identity verification using computer vision for automatic garage door opening. IEEE Transactions on Consumer Electronics, 57(2), 906-914.
Xiao, D., Zhang, L., Li, J., & Li, J. (2021). Robust license plate detection and recognition with automatic rectification. Journal of Electronic Imaging, 30(1), 013002.
Zade, M. B., & Kulkarni, S. M. (2018). Auto Vehicle Speed Control System-the Review. In 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) (pp. 1556-1559). IEEE.
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Derechos de autor 2022 Gustavo Martínez-Prado, Miguel Pescador-Hernandez, Javier García-Ponce